Alessandro Pellegrini

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1 Alessandro Pellegrini Curriculum Vitæ pellegrini Personal Information first name Alessandro last name Pellegrini place/date of birth Roma (Italy), Wednesday 7 th January, 1987 nationality Italian Work Experience December 2014 present June 2014 present Research Fellow, Sapienza, University of Rome. Researh on the design and development of algorithms for high-performance computing on multicore environments Researcher, IRIANC International Research Institute for Autonomic Network Computing Lecturer, Sapienza, University of Rome. Lecturer for the Concurrent and Parallel Programming course, in the Master s Degree Computer Architectures and Distributed Systems Lecturer, Sapienza, University of Rome. Assistant for the Computer Architectures course, in the Bachelor s Degree in Computer Science Lecturer, Sapienza, University of Rome. Assistant for the Operating Systems course, in the Bachelor s Degree in Computer Science February 2012 October 2012 July 2011 September 2011 Consultant, IES Ingegneria Elettronica Sistemi s.r.l. Project of a redundancy system for HElabor processor, and reliability assessment Consultant, Poste Italiane S.p.A. Assessment and Capacity Analysis on the Business Main Core Infrastructure Projects April 2014 present November 2008 present SIGMA, Sistema Integrato di sensori in ambiente Cloud per la Gestione Multirischio Avanzata, National Italian Project. The Integrated Sensors System in Cloud Environments for Advanced Multirisk Management (SIGMA) is a multi-layered architecture for acquiring, integrating, and elaborating heterogeneous data coming from differentiated sensor networks. Its goal is to enhance (both environmental and factory) monitoring and control systems to provide data useful for the prevention of risk situations. ROOT-Sim, The ROme OpTimistic Simulator, Open Source Software. The ROme OpTimistic Simulator is a multithread x86_64 Open Source, parallel/distributed simulation platform developed using C/POSIX technology, which is based on a simulation kernel layer that ultimately relies on MPI for data exchange. The platform transparently supports all the mechanisms associated with parallelization and optimistic synchronization. 1/8

7 Attachment 2: Summary of the Ph.D. Thesis Simulation is a powerful technique to represent the evolution of real-world phenomena or systems over time. It has been extensively used in different research fields (from medicine to biology, to economy, and to disaster rescue) to study the behaviour of complex systems during their evolution (symbiotic simulation) or before their actual realization (what-if analysis). A traditional way to achieve high performance simulations is the employment of Parallel Discrete Event Simulation (PDES) techniques, which are based on the partitioning of the simulation model into Logical Processes (LPs) that can execute events in parallel on different CPUs and/or different CPU cores, and rely on synchronization mechanisms to achieve causally consistent execution of simulation events. As it is well recognized, the optimistic synchronization approach, namely the Time Warp protocol, which is based on rollback for recovering possible timestamp-order violations due to the absence of block-until-safe policies for event processing, is likely to favour speedup in general application/architectural contexts. However, the optimistic PDES paradigm implicitly relies on a programming model that shifts from traditional sequential-style programming, given that there is no notion of global address space (fully accessible while processing events at any LP). Furthermore, there is the underlying assumption that the code associated with event handlers cannot execute unrecoverable operations given their speculative processing nature. Nevertheless, even though no unrecoverable action is ever executed by event handlers, a means to actually undo the action if requested needs to be devised and implemented within the software stack. On the other hand, sequential-style programming is an easy paradigm for the development of simulation code, given that it does not require the programmer to reason about memory partitioning (and therefore message passing) and speculative (concurrent) processing of the application. My PhD Thesis presents methodological and technical innovations which will show how it is possible, by developing innovative runtime mechanisms, to allow a programmer to implement its simulation model in a fully sequential way, and have the underlying simulation framework to execute it in parallel according to speculative processing techniques. Some of the approaches we provide show applicability in either sharedor distributed-memory systems, while others will be specifically tailored to multi/many-core architectures. We will clearly show, during the development of these supports, what is the effect on performance of these solutions, which will nevertheless be negligible, allowing a fruitful exploitation of the available computing power. In the end, we will highlight which are the clear benefits on the programming model that the model developer will experience by relying on these innovative solutions. Wednesday 21 th January, /8

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